BiPhone: Modeling Inter Language Phonetic Influences in Text

no code implementations • 6 Jul 2023 • Abhirut Gupta, Ananya B. Sai, Richard Sproat, Yuri Vasilevski, James S. Ren, Ambarish Jash, Sukhdeep S. Sodhi, Aravindan Raghuveer

To the best of our knowledge, FunGLUE is the first benchmark to introduce L1-L2 interactions in text.

HintedBT: Augmenting Back-Translation with Quality and Transliteration Hints

no code implementations • EMNLP 2021 • Sahana Ramnath, Melvin Johnson, Abhirut Gupta, Aravindan Raghuveer

For such cases, we propose training the model with additional hints (as target tags on the decoder) that provide information about the operation required on the source (translation or both translation and transliteration).

Data Augmentation NMT +2

Training Data Augmentation for Code-Mixed Translation

1 code implementation • NAACL 2021 • Abhirut Gupta, Aditya Vavre, Sunita Sarawagi

Machine translation of user-generated code-mixed inputs to English is of crucial importance in applications like web search and targeted advertising.

Data Augmentation Machine Translation +1

Improving Segmentation for Technical Support Problems

1 code implementation • ACL 2020 • Kushal Chauhan, Abhirut Gupta

We formulate the problem as a sequence labelling task, and study the performance of state of the art approaches.

Language Modelling Retrieval +3

Semantic Parsing for Technical Support Questions

no code implementations • COLING 2018 • Abhirut Gupta, Anupama Ray, Gargi Dasgupta, Gautam Singh, Pooja Aggarwal, Prateeti Mohapatra

Technical support problems are very complex.

Information Retrieval Retrieval +1

Mining Procedures from Technical Support Documents

no code implementations • 24 May 2018 • Abhirut Gupta, Abhay Khosla, Gautam Singh, Gargi Dasgupta

Existing research on question answering or intelligent chatbots does not look within procedures or deep-understand them.

Question Answering